Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	New York	20,442
2	New Jersey	19,491
3	Rhode Island	15,824
4	Massachusetts	15,780
5	District of Columbia	14,583
6	Connecticut	13,003
7	Louisiana	12,301
8	Delaware	11,682
9	Illinois	11,354
10	Maryland	11,220
11	Arizona	10,249
12	Nebraska	9,855
13	Iowa	9,151
14	Mississippi	8,926
15	South Dakota	7,591
16	Alabama	7,581
17	Virginia	7,285
18	Pennsylvania	7,073
19	Georgia	7,046
20	Michigan	7,044
21	Indiana	6,887
22	Florida	6,813
23	Utah	6,805
24	South Carolina	6,728
25	Arkansas	6,712
26	Minnesota	6,364
27	North Carolina	6,072
28	Tennessee	6,060
29	Nevada	5,834
30	New Mexico	5,714
31	California	5,669
32	Colorado	5,642
33	Texas	5,475
34	Wisconsin	5,343
35	Kansas	5,000
36	North Dakota	4,655
37	Washington	4,469
38	Ohio	4,366
39	New Hampshire	4,236
40	Missouri	3,543
41	Kentucky	3,504
42	Oklahoma	3,328
43	Idaho	3,228
44	Wyoming	2,505
45	Maine	2,394
46	Puerto Rico	2,270
47	Oregon	2,013
48	Vermont	1,935
49	West Virginia	1,601
50	Alaska	1,483
51	Montana	859
52	Hawaii	624

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	Arizona	362
2	Florida	362
3	Nevada	282
4	South Carolina	278
5	Alabama	203
6	Texas	185
7	Mississippi	168
8	Arkansas	167
9	Utah	166
10	Georgia	165
11	Louisiana	165
12	California	143
13	North Carolina	140
14	Tennessee	126
15	Delaware	122
16	Idaho	115
17	Iowa	110
18	Kansas	96
19	Nebraska	93
20	New Mexico	91
21	Wisconsin	79
22	Minnesota	73
23	Oklahoma	69
24	Ohio	68
25	South Dakota	68
26	Washington	67
27	Missouri	64
28	Virginia	63
29	Maryland	62
30	Illinois	54
31	Indiana	54
32	North Dakota	51
33	District of Columbia	50
34	Wyoming	47
35	Kentucky	46
36	Oregon	43
37	Colorado	41
38	Pennsylvania	41
39	Alaska	38
40	Puerto Rico	34
41	Massachusetts	33
42	Rhode Island	32
43	Maine	29
44	Michigan	29
45	New York	29
46	Connecticut	28
47	Montana	28
48	West Virginia	26
49	New Jersey	25
50	New Hampshire	21
51	Hawaii	8
52	Vermont	5

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	1,687
2	New York	1,600
3	Connecticut	1,211
4	Massachusetts	1,174
5	Rhode Island	892
6	District of Columbia	780
7	Louisiana	688
8	Michigan	617
9	Illinois	561
10	Maryland	525
11	Delaware	520
12	Pennsylvania	520
13	Indiana	389
14	Mississippi	355
15	Colorado	292
16	New Hampshire	269
17	Minnesota	260
18	Georgia	257
19	Ohio	241
20	New Mexico	235
21	Iowa	225
22	Arizona	219
23	Virginia	203
24	Alabama	189
25	Washington	173
26	Missouri	167
27	Nevada	163
28	Florida	160
29	California	151
30	Nebraska	141
31	South Carolina	139
32	Wisconsin	134
33	Kentucky	130
34	North Carolina	127
35	North Dakota	115
36	South Dakota	102
37	Oklahoma	97
38	Kansas	94
39	Vermont	89
40	Arkansas	87
41	Tennessee	85
42	Texas	83
43	Maine	78
44	Utah	52
45	West Virginia	51
46	Idaho	50
47	Oregon	48
48	Puerto Rico	47
49	Wyoming	34
50	Montana	20
51	Alaska	16
52	Hawaii	12

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Rhode Island	5
2	Massachusetts	4
3	Mississippi	4
4	Arizona	2
5	District of Columbia	2
6	New Jersey	2
7	Alabama	1
8	Arkansas	1
9	Connecticut	1
10	Florida	1
11	Illinois	1
12	Indiana	1
13	Kansas	1
14	Maryland	1
15	Minnesota	1
16	New York	1
17	South Carolina	1
18	South Dakota	1
19	Virginia	1
20	Alaska	0
21	California	0
22	Colorado	0
23	Delaware	0
24	Georgia	0
25	Hawaii	0
26	Idaho	0
27	Iowa	0
28	Kentucky	0
29	Louisiana	0
30	Maine	0
31	Michigan	0
32	Missouri	0
33	Montana	0
34	Nebraska	0
35	Nevada	0
36	New Hampshire	0
37	New Mexico	0
38	North Carolina	0
39	North Dakota	0
40	Ohio	0
41	Oklahoma	0
42	Oregon	0
43	Pennsylvania	0
44	Puerto Rico	0
45	Tennessee	0
46	Texas	0
47	Utah	0
48	Vermont	0
49	Washington	0
50	West Virginia	0
51	Wisconsin	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Trousdale	Tennessee	131,336	1	99
Lake	Tennessee	98,489	2	99
Dakota	Nebraska	88,785	3	99
Buena Vista	Iowa	86,340	4	99
Lincoln	Arkansas	79,699	5	99
Davidson	Tennessee	13,467	210	93
Richland	South Carolina	8,089	499	84
Orange	California	4,161	1057	66
York	South Carolina	4,114	1065	66
Pierce	Washington	3,139	1342	57

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Hancock	Georgia	3,784	1	99
Randolph	Georgia	3,688	2	99
Terrell	Georgia	3,165	3	99
Early	Georgia	3,042	4	99
Essex	New Jersey	2,529	5	99
Richland	South Carolina	197	675	78
Davidson	Tennessee	158	778	75
Pierce	Washington	108	993	68
Orange	California	104	1015	67
York	South Carolina	43	1521	51

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.